Heterogeneous Catalysis of Ozone Using Iron–Manganese Silicate for Degradation of Acrylic Acid

Iron–manganese silicate (IMS) was synthesized by chemical coprecipitation and used as a catalyst for ozonating acrylic acid (AA) in semicontinuous flow mode. The Fe-O-Mn bond, Fe-Si, and Mn-Si binary oxide were formed in IMS on the basis of the results of XRD, FTIR, and XPS analysis. The removal efficiency of AA was highest in the IMS catalytic ozonation processes (98.9% in 15 min) compared with ozonation alone (62.7%), iron silicate (IS) catalytic ozonation (95.6%), and manganese silicate catalytic ozonation (94.8%). Meanwhile, the removal efficiencies of total organic carbon (TOC) were also improved in the IMS catalytic ozonation processes. The IMS showed high stability and ozone utilization. Additionally, H₂O₂ was formed in the process of IMS catalytic ozonation. Electron paramagnetic resonance (EPR) analysis and radical scavenger experiments confirmed that hydroxyl radicals (•OH) were the dominant oxidants. Cl⁻, HCO₃⁻, PO₄³⁻, Ca²⁺, and Mg²⁺ in aqueous solution could adversely affect AA degradation. In the IMS catalytic ozonation of AA, the surface hydroxyl groups and Lewis acid sites played an important role.     

Syntheses,Structures and Photocurrent Response Properties of Two Crystals Based on Tetrathiafulvalene Derivatives

In this paper, two compounds [Zn_2~(2+)(2,6-bis(4'-pyridyl)-TTF)(TPA)_2~(2-)](1) and [Cd~(2+)(2,6(7)-bis(4'-pyridyl)-TTF)(TPA)~(2-)(H_2O)_2](TTF = tetrathiafulvalene, TPA = terephthalic acid)(2) were synthesized by using solvothermal method and characterized by single-crystal X-ray. The purity of the two compounds was confirmed by their PXRD data. We also tested the photocurrent responses of these two compounds, and found they could generate photocurrent signal when exposed to light, but the photocurrent intensity of compound 2 is significantly greater than that of 1. From the crystal structure analysis, the possible reason for this phenomenon is that 2 has a more compact ligand arrangement than 1, leading to a higher carrier density and easier excitation.     

Pyrene分子(小片石墨晶体)的电子传导特性

利用量子理论中基于Green函数的tight-binding方法,对pyrene分子的电子传导和电子流分布进行了理论研究。在考虑到界面耦合和Hopping积分的情况下,得出了电子透射谱和流分布的模拟结果。结果显示透射与电子的能量紧密相关;谱的振荡特征是能级量子化的结果;流分布有着特定的方向,并且在每一个原子点上符合Kirchhoff量子流守恒定律。另外还发现了桥接pyrene分子的正负能开关特性。     

High-performance potassium poly(heptazine imide) films for photoelectrochemical water splitting

Photoelectrochemical (PEC) water splitting is an appealing approach by which to convert solar energy into hydrogen fuel. Polymeric semiconductors have recently attracted intense interest of many scientists for PEC water splitting. The crystallinity of polymer films is regarded as the main factor that determines the conversion efficiency. Herein, potassium poly(heptazine) imide (K-PHI) films with improved crystallinity were in situ prepared on a conductive substrate as a photoanode for solar-driven water splitting. A remarkable photocurrent density of ca. 0.80 mA cm⁻² was achieved under air mass 1.5 global illumination without the use of any sacrificial agent, a performance that is ca. 20 times higher than that of the photoanode in an amorphous state, and higher than those of other related polymeric photoanodes. The boosted performance can be attributed to improved charge transfer, which has been investigated using steady state and operando approaches. This work elucidates the pivotal importance of the crystallinity of conjugated polymer semiconductors for PEC water splitting and other advanced photocatalytic applications.

Potassium poly(heptazine imide) photoanode is synthesized, and owing to the improved crystallinity, it has presented a remarkable performance for solar-driven water splitting.     

Rapid Identification for the Pterocarpus Bracelet by Three-Step Infrared Spectrum Method

In order to explore a rapid identification method for the anti-counterfeit of commercial high value collections, a three-step infrared spectrum method was used for the pterocarpus collection identification to confirm whether a commercial pterocarpus bracelet (PB) was made from the precious species of Pterocarpus santalinus (P. santalinus). In the first step, undertaken by Fourier transform infrared spectroscopy (FTIR) spectrum, the absorption peaks intensity of PB was slightly higher than that of P. santalinus only at 1594 cm⁻¹, 1205 cm⁻¹, 1155 cm⁻¹ and 836 cm⁻¹. In the next step of second derivative IR spectra (SDIR), the FTIR features of the tested samples were further amplified, and the peaks at 1600 cm⁻¹, 1171 cm⁻¹ and 1152 cm⁻¹ become clearly defined in PB. Finally, by means of two-dimensional correlation infrared (2DIR) spectrum, it revealed that the response of holocellulose to thermal perturbation was stronger in P. santalinus than that in PB mainly at 977 cm⁻¹, 1008 cm⁻¹, 1100 cm⁻¹, 1057 cm⁻¹, 1190 cm⁻¹ and 1214 cm⁻¹, while the aromatic functional groups of PB were much more sensitive to the thermal perturbation than those of P. santalinus mainly at 1456 cm⁻¹, 1467 cm⁻¹, 1518 cm⁻¹, 1558 cm⁻¹, 1576 cm⁻¹ and 1605 cm⁻¹. In addition, fluorescence microscopy was used to verify the effectiveness of the above method for wood identification and the results showed good consistency. This study demonstrated that the three-step IR method could provide a rapid and effective way for the anti-counterfeit of pterocarpus collections.     

Structural and Functional Analysis of the Pyridoxal Phosphate Homeostasis Protein YggS from Fusobacterium nucleatum

Pyridoxal 5′-phosphate (PLP) is the active form of vitamin B6, but it is highly reactive and poisonous in its free form. YggS is a PLP-binding protein found in bacteria and humans that mediates PLP homeostasis by delivering PLP to target enzymes or by performing a protective function. Several biochemical and structural studies of YggS have been reported, but the mechanism by which YggS recognizes PLP has not been fully elucidated. Here, we report a functional and structural analysis of YggS from Fusobacterium nucleatum (FnYggS). The PLP molecule could bind to native FnYggS, but no PLP binding was observed for selenomethionine (SeMet)-derivatized FnYggS. The crystal structure of FnYggS showed a type III TIM barrel fold, exhibiting structural homology with several other PLP-dependent enzymes. Although FnYggS exhibited low (<35%) amino acid sequence similarity with previously studied YggS proteins, its overall structure and PLP-binding site were highly conserved. In the PLP-binding site of FnYggS, the sulfate ion was coordinated by the conserved residues Ser201, Gly218, and Thr219, which were positioned to provide the binding moiety for the phosphate group of PLP. The mutagenesis study showed that the conserved Ser201 residue in FnYggS was the key residue for PLP binding. These results will expand the knowledge of the molecular properties and function of the YggS family.     

EGFAFS: A Novel Feature Selection Algorithm Based on Explosion Gravitation Field Algorithm

Feature selection (FS) is a vital step in data mining and machine learning, especially for analyzing the data in high-dimensional feature space. Gene expression data usually consist of a few samples characterized by high-dimensional feature space. As a result, they are not suitable to be processed by simple methods, such as the filter-based method. In this study, we propose a novel feature selection algorithm based on the Explosion Gravitation Field Algorithm, called EGFAFS. To reduce the dimensions of the feature space to acceptable dimensions, we constructed a recommended feature pool by a series of Random Forests based on the Gini index. Furthermore, by paying more attention to the features in the recommended feature pool, we can find the best subset more efficiently. To verify the performance of EGFAFS for FS, we tested EGFAFS on eight gene expression datasets compared with four heuristic-based FS methods (GA, PSO, SA, and DE) and four other FS methods (Boruta, HSICLasso, DNN-FS, and EGSG). The results show that EGFAFS has better performance for FS on gene expression data in terms of evaluation metrics, having more than the other eight FS algorithms. The genes selected by EGFAGS play an essential role in the differential co-expression network and some biological functions further demonstrate the success of EGFAFS for solving FS problems on gene expression data.     

A Novel Method for Pattern Recognition of GIS Partial Discharge via Multi-Information Ensemble Learning

Partial discharge (PD) is the main feature that effectively reflects the internal insulation defects of gas-insulated switchgear (GIS). It is of great significance to diagnose the types of insulation faults by recognizing PD to ensure the normal operation of GIS. However, the traditional diagnosis method based on single feature information analysis has a low recognition accuracy of PD, and there are great differences in the diagnosis effect of various insulation defects. To make the most of the rich insulation state information contained in PD, we propose a novel multi-information ensemble learning for PD pattern recognition. First, the ultra-high frequency and ultrasonic data of PD under four typical defects of GIS are obtained through experiment. Then the deep residual convolution neural network is used to automatically extract discriminative features. Finally, multi-information ensemble learning is used to classify PD types at the decision level, which can complement the shortcomings of the independent recognition of the two types of feature information and has higher accuracy and reliability. Experiments show that the accuracy of the proposed method can reach 97.500%, which greatly improves the diagnosis accuracy of various insulation defects.     

Facile Fabrication of 1-Methylimidazole/Cu Nanozyme with Enhanced Laccase Activity for Fast Degradation and Sensitive Detection of Phenol Compounds

Facile construction of functional nanomaterials with laccase-like activity is important in sustainable chemistry since laccase is featured as an efficient and promising catalyst especially for phenolic degradation but still has the challenges of high cost, low activity, poor stability and unsatisfied recyclability. In this paper, we report a simple method to synthesize nanozymes with enhanced laccase-like activity by the self-assembly of copper ions with various imidazole derivatives. In the case of 1-methylimidazole as the ligand, the as-synthesized nanozyme (denoted as Cu-MIM) has the highest yield and best activity among the nanozymes prepared. Compared to laccase, the K_m of Cu-MIM nanozyme to phenol is much lower, and the v_max is 6.8 times higher. In addition, Cu-MIM maintains excellent stability in a variety of harsh environments, such as high pH, high temperature, high salt concentration, organic solvents and long-term storage. Based on the Cu-MIM nanozyme, we established a method for quantitatively detecting phenol concentration through a smartphone, which is believed to have important applications in environmental protection, pollutant detection and other fields.     

Precise electro-reduction of alkyl halides for radical defluorinative alkylation

Reported here is a precise electro-reduction strategy for radical defluorinative alkylation towards the synthesis of gem-difluoroalkenes from α-trifluoromethylstyrenes. According to the redox-potential difference of the radical precursors, direct or indirect electrolysis is respectively adopted to realize the precise reduction. An easy-to-handle, catalyst-and metal-free condition is developed for the reduction of alkyl radical precursors that are generally easier to be reduced than α-trifluorome...